Experimental Settings –
We evaluate FedLAMA using three representative benchmark datasets: CIFAR-10 (ResNet20 ([1]})), CIFAR-100 (WideResNet28-10 ([2]})), and Federated Extended MNIST (CNN ([3]})).
We use TensorFlow 2.4.3 for local training and MPI for model aggregation.
All our experiments are conducted on 4 compute nodes each of which has 2 NVIDIA v100 GPUs.
